Integration of GIS-based Multi-criteria Analysis Techniques for the Delineation of Groundwater Potential Zones in Oyo state, Nigeria using Bayes’ Approach

Epuh E. E.*, Famiwaye O. V., Daramola O. E., Orji J. M. and Owolabi O. A.

Department of Surveying and Geoinformatics, University of Lagos, Lagos, Nigeria

*Corresponding Author: eepuh@unilag.edu.ng

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 Vol. 6 No. 1  | March 2022 | Pages 246 – 269 |   Cite this article

https://doi.org/10.36263/nijest.2022.01.0325

Abstract

ABSTRACT

Groundwater is the world’s most extracted raw material due to its incessant need for human consumption. This study was carried out to delineate groundwater potential zones in Oyo state, Nigeria using the integration of two GIS-based multi-criteria analysis techniques – Multi influencing factor (MIF) and Analytic hierarchy process (AHP). The Bayes’ integration approach for the recalculation of criteria weights was used. Eight groundwater potential contributing factors such as land cover, drainage density, lineament density, soil texture, geology, geomorphology, slope, and rainfall were processed and the multi-criteria analysis techniques were employed in assigning weights to each thematic layer and sub-classes. The thematic layers were overlaid in ArcGIS 10.4 software environment using the groundwater potential index equation for the generation of groundwater potential maps. The criteria weights of the MIF and AHP techniques were further integrated using Bayes’ approach to obtain an optimum groundwater potential map. In this study, the groundwater potential maps from the three techniques were validated using the Receiver Operating Characteristics (ROC) curve methods. The validation of the groundwater potential zonation maps from the MIF, AHP and the Bayes’ integration was also executed by evaluating the depths and yields from 1425 boreholes distributed across the study area. The Bayes’ approach shows that the groundwater percentage distributions within the study area are: very low (36%), low (34%), Moderate (14%) and high (16%). The maximum yields of 200m3 were observed in Akinyele, Atisbo and Egbeda LGA with minimum borehole depths of 24.20m, 30.30m and 30.00m. The Area under the Curve (AUC) results are: MIF (69.4%), Bayes’ (69.0%) and AHP (67.6%) respectively. The Bayes’ integration approach further shows better consistency as the average borehole yields across the groundwater potential zones positively correlates i.e. high potential zone has the highest average borehole yield, followed by the moderate, low and very low.

Keywords: Groundwater potential, Multi influencing factor, Analytic hierarchy process, GIS, Bayes’ approach

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Epuh E. E., Famiwaye O. V., Daramola O. E., Orji J. M. and Owolabi O. A., 2022. Integration of GIS-based Multi-Criteria Analysis Techniques for the Delineation of Groundwater Potential Zones in Oyo state, Nigeria using Bayes’ Approach. Nigerian Journal of Environmental Sciences and Technology, 6(1), pp. 246-269.
https://doi.org/10.36263/nijest.2022.01.0325


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